There are billions of electronically communicating devices in use. Many of these devices are wireless devices such as smartphones, tablets, personal computers (PCs), media players and readers, personal digital assistants (PDAs), headsets, cameras, vehicles, wearable fitness device, health monitoring devices, and so forth. Many of these devices use some form of electromagnetic (EM) or radio frequency (RF) technology for communications with other devices, various communications services, and the Internet. Many of these devices wirelessly connect to the Internet forming a growing “Internet of Things” (IoT). The number of electronically communicating devices is expected continue to multiply due to business and consumer demands.
Despite the growing ubiquity of IoT devices, these devices and the networks connecting them remain vulnerable to wireless attacks. One driver in IoT device vulnerability is that there is no dominant IoT wireless networking standard. Instead, IoT devices employ one of many wireless access protocols. Some of these protocols are openly defined for anyone to use, others are proprietary to specific manufacturers. Because of this heterogeneity, IoT networks have been constructed with a primary objective of efficiently implementing stable wireless connectivity and generally assume that the wireless operating environment will be absent of threats from malicious agents. As speed and stability have been primary concerns, there has been little attention focused on the security of IoT wireless networks and their components. This reliance on implicit trust leaves wireless networks and the connected nodes vulnerable to external attacks.
IoT wireless protocols define how nodes operate on the network and may provide a gateway for entry to existing wired networks. Malicious agents may exploit these protocols to gain network access and possibly engage in undesirable network activities. Ill-defined protocols or misconfigured configured network nodes can cause harm either unintentionally due to poor user operation or intentionally by allowing access to malicious agents.
An example malicious objective may be to degrade the target network performance, or ultimately deny service to legitimate users. Another example may be to extract situational awareness about the target network. Yet another example may be to extract sensitive information from the target network. Other goals of malicious actors may include impacting network routing to prevent certain packets from reaching their intended destination or acting as an authenticated node by evading network trust mechanisms.
Emerging adaptable link layer protocols, such cognitive radio, may impact both attack and defense paradigms. Highly agile medium access, which may adapt due to context or environment, may result in wireless network nodes that are even more susceptible to attacks that exploit unforeseen vulnerabilities. Under this emerging paradigm, spatial dynamics may play a large role in how the network forms and operates.
There is a need in the art for blind signal classification and demodulation in multimodal RF environments to support detection, location, and classification of wireless attacks against IoT networks and devices. Such technologies can support the implementation of security measures related to collecting and processing electromagnetic, radio frequency emission signatures from electronic devices for identifying potential wireless network security threats.